Scholar
Artur Yakimovich
Google Scholar ID: PgWk6woAAAAJ
CASUS, HZDR
Citations & Impact
Citations
919
H-index
20
i10-index
22
Publications
20
Co-authors
11
list available
Contact
Publications
Resume (English only)
Academic Achievements
- Wyrzykowska, Maria, et al. 'A Benchmark for Virus Infection Reporter Virtual Staining in Fluorescence and Brightfield Microscopy.' bioRxiv (2024).
- De, Trina, Vardan Andriasyan, and Artur Yakimovich. 'PyPlaque: an Open-source Python Package for Phenotypic Analysis of Virus Plaque Assays.' bioRxiv (2024).
- Li, Rui, et al. 'Denoising, Deblurring, and optical Deconvolution for cryo-ET and light microscopy with a physics-informed deep neural network DeBCR.' bioRxiv (2024).
- della Maggiora, Gabriel, et al. 'Single Exposure Quantitative Phase Imaging with a Conventional Microscope using Diffusion Models.' arXiv preprint arXiv:2406.04388 (2024).
- Li, Rui, Gabriel della Maggiora, Vardan Andriasyan, Anthony Petkidis, Artsemi Yushkevich, Mikhail Kudryashev, and Artur Yakimovich. 'Microscopy image reconstruction with physics-informed denoising diffusion probabilistic model.' arXiv preprint arXiv:2306.02929 (2023).
- Li, Rui, Mikhail Kudryashev, and Artur Yakimovich. 'Solving the inverse problem of microscopy deconvolution with a residual Beylkin-Coifman-Rokhlin neural network.' ECCV (2024).
- Della Maggiora, Gabriel, et al. 'Conditional Variational Diffusion Models.' The Twelfth International Conference on Learning Representations. 2023.
- Sharma, Vaibhav, and Artur Yakimovich. 'A deep learning dataset for sample preparation artefacts detection in multispectral high-content microscopy.' Scientific Data (2024).
- Liou, Natasha, et al. 'A clinical microscopy dataset to develop a deep learning diagnostic test for urinary tract infection.' Scientific Data (2024).
- Li, Rui, Mikhail Kudryashev, and Artur Yakimovich. 'A weak-labelling and deep learning approach for in-focus object segmentation in 3D widefield microscopy.' Scientific Reports (2023).
- Sharma, Vaibhav, and Artur Yakimovich. 'Phenotype-preserving metric design for high-content image reconstruction by generative inpainting.' Emerging Topics in Artificial Intelligence (ETAI) 2023. Vol. 12655. SPIE (2023).
- Li, Rui, et al. 'Open-Source Biomedical Image Analysis Models: A Meta-Analysis and Continuous Survey.' Frontiers in Bioinformatics (2022): 76.
- Galimov, Evgeniy, and Artur Yakimovich. 'A tandem segmentation-classification approach for the localization of morphological predictors of C. elegans lifespan and motility.' Aging (Albany NY) 14.4 (2022): 1665.
Research Experience
- Serves as the Group Leader of the Machine Learning for Infection and Disease (MLID) group (also known as Yakimovich group).
Background
- Focused on developing the latest Machine Learning and Computer Science methods to facilitate our understanding of Infection Biology and Disease Biology.
Miscellany
- Follow the team on Twitter via the hashtag #YakimovichGroup.
